tf.linalg.LinearOperatorZeros

Computes the matrix logarithm of one or more square matrices:

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Compat aliases for migration

tf.compat.v1.linalg.logm

tf.linalg.logm(
    input, name=None
)

\(log(exp(A)) = A\)

This op is only defined for complex matrices. If A is positive-definite and real, then casting to a complex matrix, taking the logarithm and casting back to a real matrix will give the correct result.

This function computes the matrix logarithm using the Schur-Parlett algorithm. Details of the algorithm can be found in Section 11.6.2 of: Nicholas J. Higham, Functions of Matrices: Theory and Computation, SIAM 2008. ISBN 978-0-898716-46-7.

The input is a tensor of shape [..., M, M] whose inner-most 2 dimensions form square matrices. The output is a tensor of the same shape as the input containing the exponential for all input submatrices [..., :, :].

Args
`input`	A `Tensor`. Must be one of the following types: `complex64`, `complex128`. Shape is `[..., M, M]`.
`name`	A name for the operation (optional).

Returns
A `Tensor`. Has the same type as `input`.

TensorFlow

tf.linalg / LinearOperatorZeros

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tf.linalg / LinearOperatorZeros

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